Effects of temperature and salinity on survival of young-of-the-year Hudson River striped bass (<i>Morone saxatilis</i>): implications for optimal overwintering habitats
Bibliographic record
Abstract
We examined the role of salinity, body size, and energetic state in determining low temperature tolerance of young-of-the-year (YOY) striped bass (Morone saxatilis) and used this information to map optimal overwintering habitat in the Hudson River estuary. A long-term experiment compared survival at 15 ppt and 30 ppt. In additional experiments, winter-acclimated fish were exposed to temperature declines (2.3°C·day1to 1°C·week1) at salinities from 0 ppt to 35 ppt. Highest survival at low temperatures was consistently observed at intermediate salinities. These results suggest that the observed distribution of overwintering striped bass is related to physiological constraints on osmo regulatory ability at low temperatures. Low temperature tolerance appeared unrelated to body size and energetic state. Salinity profiles were used to describe the location and extent of optimal wintering habitats under various hydrographic regimes. The location of optimal habitats was displaced by over 27 km along the river axis because of variation in salinity regime. Changes in the availability of optimal habitat may be responsible for variation in recruitment to the Hudson River population. These results demonstrate the need to consider a holistic approach encompassing all seasons of the year in assessing habitat requirements of fishes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".